The microfinance community has given a commitment to reach 100 million of the poorest people throughout the world by 2005. “Poorest” in this context has been defined in economic terms as the number of individuals living below the ‘$1 a day’ poverty line (Microcredit Summit Campaign 2002).
The Millennium Development Goals have posed additional challenges to microfinance organisations (MFOs), as poverty eradication targets have been set according to improvements in a broad selection of welfare indicators (Littlefield, Morduch and Hashemi 2003). Increasingly, donor resources are being channelled to meet international poverty eradication targets. This has placed MFOs under pressure to substantiate claims about levels of poverty outreach and positive improvements in client well-being. The effectiveness of such impact monitoring is contingent upon the quality and availability of empirical data.
Until recently, there has been a paucity of simple instruments that could collect information on client well-being reliably and at low cost (Morduch 1999). However, concerted efforts have been made to improve the quality of poverty assessments in the microfinance sector. Methods include external poverty assessments, an example being the Poverty Assessment Tool (Zeller et al. 2001). In addition, MFOs have developed internal poverty monitoring and targeting instruments including a Participatory Wealth Ranking (PWR) and the Housing Index (Simanowitz 2000). However, opportunities to aggregate the poverty profiles of clients generated by local level poverty assessments remain limited. Both external poverty assessments and internal organisational poverty measures are relative measures of poverty, comparing the well-being of clients to non-clients. Most of these instruments measure broad dimensions of poverty based upon a basket of locally specific indicators and they seldom incorporate money metric measures. This prevents comparison with national or international poverty profiles.
In an attempt to find a solution to this limitation, this article has three objectives: firstly to evaluate the reliability of local relational poverty assessments; secondly to identify indicators that are relevant to both local and national contexts, therefore enabling both relational and absolute poverty measurement to take place; and third to match local poverty assessments to national and international absolute poverty measures. This research uses data previously gathered at the Small Enterprise Foundation (SEF), an MFO in the Limpopo Province of South Africa, using PWR. In addition, an independent survey using the Poverty Assessment Tool (PAT) was conducted in October 2000 in which relative poverty scores were added which was matched to the PWR poverty scores (van de Ruit et al. 2001). Finally, absolute poverty levels of households with similar scores have been estimated using a national Income and Expenditure Survey (IES), also conducted in October 2000.
This article comes from the IDS Bulletin 34.4 (2003) 2. Triangulating Qualitative and Quantitative Approaches to the Measurement of Poverty: A Case Study in Limpopo Province, South Africa